Accession Number:

AD1034035

Title:

Channel Compensation for Speaker Recognition using MAP Adapted PLDA and Denoising DNNs

Descriptive Note:

Technical Report

Corporate Author:

MIT Lincoln Laboratory Lexington United States

Report Date:

2016-06-21

Pagination or Media Count:

6.0

Abstract:

Over several decades, speaker recognition performance has steadily improved for applications using telephone speech. A big part of this improvement has been the availability of large quantities of speaker-labeled data from telephone recordings. For new data applications, such as audio from room microphones, we would like to effectively use existing telephone data to build systems with high accuracy while maintaining good performance on existing telephone tasks. In this paper we compare and combine approaches to compensate models parameters and features for this purpose. For model adaptation we explore MAP adaptation of hyper-parameters and for feature compensation we examine the use of denoising DNNs. On a multi-room, multi-microphone speaker recognition experiment we show a reduction of 61 in EER with a combination of these approaches while slightly improving performance on telephone data.

Subject Categories:

  • Voice Communications

Distribution Statement:

APPROVED FOR PUBLIC RELEASE